Influence of tumour micro-environment heterogeneity on therapeutic response

LncRNA MEG3 Inhibits Tumor Progression by Modulating Macrophage Phenotypic Polarization via miR-145-5p/DAB2 Axis in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is the predominant histological type of primary liver cancer, which ranks sixth among the most common human tumors. Tumor-associated macrophages (TAMs) are an important component of tumor microenvironment (TME) and the M2 macrophage polarization substantially contributes to tumor growth and metastasis. Long non-coding RNA (lncRNA) MEG3 was reported to restrain HCC development. However, whether MEG3 regulates macrophage phenotypic polarization in HCC remains unclear.

Methods

Bone marrow derived macrophages (BMDMs) were treated with LPS/IFNγ and IL4/IL13 to induce the M1 and M2 macrophage polarization, respectively. M2-polarized BMDMs were simultaneously transfected with adenovirus vector overexpressing MEG3 (Adv-MEG3). Subsequently, M2-polarized BMDMs were cultured for 24 h with serum-free medium, the supernatants of which were harvested as conditioned medium (CM). HCC cell line Huh7 was cultured with CM for 24 h. F4/80⁺CD68⁺ and F4/80⁺CD206⁺ cell percentages in M1-and M2-polarized BMDMs were calculated using flow cytometry. Huh7 cell migration, invasion and angiogenesis were determined via Transwell assay and tube formation experiment. Nude mice were implanted with Huh7 cells and Adv-MEG3-transfected M2-polarizd BMDMs, and tumor growth and M2 macrophage polarization markers were assessed. The binding between miR-145-5p and MEG3 or disabled-2 (DAB2) was verified by luciferase reporter assay.

Results

MEG3 presented lower expression in HCC tissues than in normal controls, and low expression of MEG3 was correlated to poorer prognosis of HCC patients. MEG3 expression was enhanced during LPS/IFNγ-induced M1 polarization, but was reduced during IL4/IL13-induced M2 polarization. MEG3 overexpression inhibited the expression of M2 polarization markers in both M2-polarized BMDMs and mice. Mechanically, MEG3 bound with miR-145-5p to regulate DAB2 expression. Overexpressing MEG3 suppressed M2 polarization-induced HCC cell metastasis and angiogenesis by upregulating DAB2 and inhibited in vivo tumor growth.

Conclusion

LncRNA MEG3 curbs HCC development by repressing M2 macrophage polarization via miR-145-5p/DAB2 axis.

Early stage gastric adenocarcinoma: clinical and molecular landscapes

Gastric adenocarcinoma, even when diagnosed at an early (localized) disease stage, poses a major health-care burden with cure rates that remain unsatisfactorily low, particularly in Western countries. This lack of progress reflects, among other aspects, the impracticality of early diagnosis, considerable variations in therapeutic approaches that is partly based on regional preferences, and the ingrained heterogeneity of gastric adenocarcinoma cells and their associated tumour microenvironment (TME). Clinical trials have long applied empirical interventions with the assumption that all early stage gastric adenocarcinomas are alike. Despite certain successes, the shortcomings of these approaches can potentially be overcome by targeting the specific molecular subsets of gastric adenocarcinomas identified by genomic and/or multi-omics analyses, including microsatellite instability-high, Epstein-Barr virus-induced, DNA damage repair-deficient, HER2-positive and PD-L1-high subtypes. Future approaches, including the availability of sophisticated vaccines, novel antibody technologies, agents targeting TME components (including fibroblasts, macrophages, cytokines or chemokines, and T cells) and novel immune checkpoint inhibitors, supported by improved tissue-based and blood-based diagnostic assays, seem promising. In this Review, we highlight current knowledge of the molecular and cellular biology of gastric adenocarcinomas, summarize the current approaches to clinical management of the disease, and consider the role of novel management and/or treatment strategies.

Long non-coding RNAs in non-small cell lung cancer: implications for EGFR-TKI resistance

Non-small cell lung cancer (NSCLC) is one of the most common types of malignant tumors as well as the leading cause of cancer-related deaths in the world. The application of epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) has dramatically improved the prognosis of NSCLC patients who harbor EGFR mutations. However, despite an excellent initial response, NSCLC inevitably becomes resistant to EGFR-TKIs, leading to irreversible disease progression. Hence, it is of great significance to shed light on the molecular mechanisms underlying the EGFR-TKI resistance in NSCLC. Long non-coding RNAs (lncRNAs) are critical gene modulators that are able to act as oncogenes or tumor suppressors that modulate tumorigenesis, invasion, and metastasis. Recently, extensive evidence demonstrates that lncRNAs also have a significant function in modulating EGFR-TKI resistance in NSCLC. In this review, we present a comprehensive summary of the lncRNAs involved in EGFR-TKI resistance in NSCLC and focus on their detailed mechanisms of action, including activation of alternative bypass signaling pathways, phenotypic transformation, intercellular communication in the tumor microenvironment, competing endogenous RNAs (ceRNAs) networks, and epigenetic modifications. In addition, we briefly discuss the limitations and the clinical implications of current lncRNAs research in this field.

Induction of glioblastoma cell ferroptosis using combined treatment with chloramphenicol and 2-deoxy-D-glucose

Glioblastoma, a malignant tumor, has no curative treatment. Recently, mitochondria have been considered a potential target for treating glioblastoma. Previously, we reported that agents initiating mitochondrial dysfunction were effective under glucose-starved conditions. Therefore, this study aimed to develop a mitochondria-targeted treatment to achieve normal glucose conditions. This study used U87MG (U87), U373, and patient-derived stem-like cells as well as chloramphenicol (CAP) and 2-deoxy-D-glucose (2-DG). We investigated whether CAP and 2-DG inhibited the growth of cells under normal and high glucose concentrations. In U87 cells, 2-DG and long-term CAP administration were more effective under normal glucose than high-glucose conditions. In addition, combined CAP and 2-DG treatment was significantly effective under normal glucose concentration in both normal oxygen and hypoxic conditions; this was validated in U373 and patient-derived stem-like cells. 2-DG and CAP acted by influencing iron dynamics; however, deferoxamine inhibited the efficacy of these agents. Thus, ferroptosis could be the underlying mechanism through which 2-DG and CAP act. In conclusion, combined treatment of CAP and 2-DG drastically inhibits cell growth of glioblastoma cell lines even under normal glucose conditions; therefore, this treatment could be effective for glioblastoma patients.

Generation, evolution, interfering factors, applications, and challenges of patient-derived xenograft models in immunodeficient mice

Establishing appropriate preclinical models is essential for cancer research. Evidence suggests that cancer is a highly heterogeneous disease. This follows the growing use of cancer models in cancer research to avoid these differences between xenograft tumor models and patient tumors. In recent years, a patient-derived xenograft (PDX) tumor model has been actively generated and applied, which preserves both cell-cell interactions and the microenvironment of tumors by directly transplanting cancer tissue from tumors into immunodeficient mice. In addition to this, the advent of alternative hosts, such as zebrafish hosts, or in vitro models (organoids and microfluidics), has also facilitated the advancement of cancer research. However, they still have a long way to go before they become reliable models. The development of immunodeficient mice has enabled PDX to become more mature and radiate new vitality. As one of the most reliable and standard preclinical models, the PDX model in immunodeficient mice (PDX-IM) exerts important effects in drug screening, biomarker development, personalized medicine, co-clinical trials, and immunotherapy. Here, we focus on the development procedures and application of PDX-IM in detail, summarize the implications that the evolution of immunodeficient mice has brought to PDX-IM, and cover the key issues in developing PDX-IM in preclinical studies.

Transcriptome sequencing and single-cell sequencing analysis identify GARS1 as a potential prognostic and immunotherapeutic biomarker for multiple cancers, including bladder cancer

Background

Glycyl-tRNA synthetase 1 (GARS1) belongs to the aminoacyl-tRNA synthetase family, playing a crucial role in protein synthesis. Previous studies have reported a close association between GARS1 and various tumors. However, the role of GARS1 in human cancer prognosis and its impact on immunology remain largely unexplored.

Methods

In this study, we comprehensively analyzed GARS1 expression at the mRNA and protein levels, examined genetic alterations, and assessed its prognostic implications in pan-cancer, with a specific emphasis on the immune landscape. Furthermore, we investigated the functional enrichment of genes related to GARS1 and explored its biological functions using single-cell data. Finally, we conducted cellular experiments to validate the biological significance of GARS1 in bladder cancer cells.

Results

In general, GARS1 expression was significantly upregulated across multiple cancer types, and it demonstrated prognostic value in various cancers. Gene Set Enrichment Analysis (GSEA) revealed the association of GARS1 expression with multiple immune regulatory pathways. Moreover, GARS1 exhibited significant correlations with immune infiltrating cells (such as DC, CD8⁺T cells, Neutrophils, and Macrophages), immune checkpoint genes (CD274, CD276), and immune regulatory factors in tumors. Additionally, we observed that GARS1 could effectively predict the response to anti-PD-L1 therapy. Notably, Ifosfamide, auranofin, DMAPT, and A-1331852 emerged as potential therapeutic agents for GARS1-upregulated tumors. Our experimental findings strongly suggest that GARS1 promotes the proliferation and migration of bladder cancer cells.

Conclusion

GARS1 holds promise as a potential prognostic marker and therapeutic target for pan-cancer immunotherapy, offering valuable insights for the development of more precise and personalized approaches to tumor treatment in the future.

Surface Stiffness Has No Impact on MCF-7 Sensitivity to Doxorubicin

Resistance to the chemotherapeutic agents in the clinical management of cancer remains a significant challenge, and the mechanical environment of cancer cells is one of the major determinants of this. Stiffening of the environment is usually associated with increased chemoresistance of cancer cells, although this process depends on the type of cancer. Breast cancer is the most frequently diagnosed cancer, and more than half a million people die from it each year worldwide. In this study, we used the most frequent (70% of diagnosed cases) breast cancer phenotype, representing the MCF-7 cell line, to investigate the influence of surface stiffness on its sensitivity to one of the most commonly used anticancer drugs-doxorubicin. We showed that the mechanical environment affected MCF-7 proliferation, adhesion, and the expression and activation of mitogen-activated protein kinases (MAPKs). Furthermore, the role of MAPKs in response to doxorubicin was dependent on surface stiffness; nevertheless, surface stiffness did not affect MCF-7 resistance to doxorubicin.

Structure-function crosstalk in liver cancer research: Protein structuromics

Liver cancer can be primary (starting in the liver) or secondary (cancer that has spread from elsewhere to the liver, known as liver metastasis). Liver metastasis is more common than primary liver cancer. Despite great advances in molecular biology methods and treatments, liver cancer is still associated with a poor survival rate and a high death rate, and there is no cure. Many questions remain regarding the mechanisms of liver cancer occurrence and development as well as tumor reoccurrence after treatment. In this study, we assessed the protein structural features of 20 oncogenes and 20 anti-oncogenes via protein structure and dynamic analysis methods and 3D structural and systematic analyses of the structure-function relationships of proteins. Our aim was to provide new insights that may inform research on the development and treatment of liver cancer.

Epigenetic and Immunological Features of Bladder Cancer

Bladder cancer (BLCA) is one of the most common types of malignant tumors of the urogenital system in adults. Globally, the incidence of BLCA is more than 500,000 new cases worldwide annually, and every year, the number of registered cases of BLCA increases noticeably. Currently, the diagnosis of BLCA is based on cystoscopy and cytological examination of urine and additional laboratory and instrumental studies. However, cystoscopy is an invasive study, and voided urine cytology has a low level of sensitivity, so there is a clear need to develop more reliable markers and test systems for detecting the disease with high sensitivity and specificity. Human body fluids (urine, serum, and plasma) are known to contain significant amounts of tumorigenic nucleic acids, circulating immune cells and proinflammatory mediators that can serve as noninvasive biomarkers, particularly useful for early cancer detection, follow-up of patients, and personalization of their treatment. The review describes the most significant advances in epigenetics of BLCA.

Analysis of Tumor Heterogeneity Through AXL Activation in Primary Resistance to EGFR Tyrosine Kinase Inhibitors

Introduction

EGFR tyrosine kinase inhibitors are standard therapeutic agents for patients with advanced NSCLC harboring EGFR mutations. Nevertheless, some patients exhibit primary resistance to EGFR tyrosine kinase inhibitors in the first-line treatment setting. AXL, a member of the TYRO3, AXL, and MERTK family of receptor tyrosine kinases, is involved in primary resistance to EGFR tyrosine kinase inhibitors in EGFR-mutated NSCLC.

Methods

We investigated spatial tumor heterogeneity using autopsy specimens and a patient-derived cell line from a patient with EGFR-mutated NSCLC having primary resistance to erlotinib plus ramucirumab.

Results

Quantitative polymerase chain reaction analysis revealed that AXL mRNA expression differed at each metastatic site. In addition, AXL expression levels were likely to be negatively correlated with the effectiveness of erlotinib plus ramucirumab therapy. Analysis of a patient-derived cell line established from the left pleural effusion before initiation of treatment revealed that the combination of EGFR tyrosine kinase inhibitors and an AXL inhibitor remarkably inhibited cell viability and increased cell apoptosis in comparison with EGFR tyrosine kinase inhibitor monotherapy or combination therapy of these inhibitors with ramucirumab.

Conclusions

Our observations suggest that AXL expression may play a critical role in the progression of spatial tumor heterogeneity and primary resistance to EGFR tyrosine kinase inhibitors in patients with EGFR-mutated NSCLC.

Making In Vitro Tumor Models Whole Again

As a reductionist approach, patient-derived in vitro tumor models are inherently still too simplistic for personalized drug testing as they do not capture many characteristics of the tumor microenvironment (TME), such as tumor architecture and stromal heterogeneity. This is especially problematic for assessing stromal-targeting drugs such as immunotherapies in which the density and distribution of immune and other stromal cells determine drug efficacy. On the other end, in vivo models are typically costly, low-throughput, and time-consuming to establish. Ex vivo patient-derived tumor explant (PDE) cultures involve the culture of resected tumor fragments that potentially retain the intact  TME of the original tumor. Although developed decades ago, PDE cultures have not been widely adopted likely because of their low-throughput and poor long-term viability. However, with growing recognition of the importance of patient-specific TME in mediating drug response, especially in the field of immune-oncology, there is an urgent need to resurrect these holistic cultures. In this Review, the key limitations of patient-derived tumor explant cultures are outlined and technologies that have been developed or could be employed to address these limitations are discussed. Engineered holistic tumor explant cultures may truly realize the concept of personalized medicine for cancer patients.

Developing a definition of immune exclusion in cancer: results of a modified Delphi workshop

Checkpoint inhibitors represent an effective treatment approach for a variety of cancers through their inhibition of immune regulatory pathways within the tumor microenvironment (TME). Unfortunately only a minority of patients with cancer achieve clinical benefit from immunotherapy, with the TME emerging as an important predictor of outcomes and sensitivity to therapy. The extent and pattern of T-cell infiltration can vary prominently within/across tumors and represents a biological continuum. Three immune profiles have been identified along this continuum: 'immune-desert' or 'T-cell cold' phenotype, 'immune-active', 'inflamed', or 'T-cell hot' phenotype, and 'immune excluded' phenotype. Of the three profiles, immune excluded remains the most ill-defined with no clear, universally accepted definition even though it is commonly associated with lack of response to immune checkpoint inhibitors and poor clinical outcomes. To address this, 16 multidisciplinary cancer experts from around the world were invited to participate in a symposium using a three-round modified Delphi approach. The first round was an open-ended questionnaire distributed via email and the second was an in-person discussion of the first round results that allowed for statements to be revised as necessary to achieve a maximum consensus (75% agreement) among the rating committee (RC). The final round questionnaire was distributed to the RC via email and had a 100% completion rate. The Delphi process resulted in moving us closer to a consensus definition for immune exclusion that is practical, clinically pertinent, and applicable across a wide range of cancer histologies. A general consensus of the role of immune exclusion in resistance to checkpoint therapy and five research priorities emerged from this process. Together, these tools could help efforts designed to address the underlying mechanisms of immune exclusion that span cancer types and, ultimately, aid in the development of treatments to target these mechanisms to improve patient outcomes.

Lung cancer lesion detection in histopathology images using graph-based sparse PCA network

Early detection of lung cancer is critical for improvement of patient survival. To address the clinical need for efficacious treatments, genetically engineered mouse models (GEMM) have become integral in identifying and evaluating the molecular underpinnings of this complex disease that may be exploited as therapeutic targets. Assessment of GEMM tumor burden on histopathological sections performed by manual inspection is both time consuming and prone to subjective bias. Therefore, an interplay of needs and challenges exists for computer-aided diagnostic tools, for accurate and efficient analysis of these histopathology images. In this paper, we propose a simple machine learning approach called the graph-based sparse principal component analysis (GS-PCA) network, for automated detection of cancerous lesions on histological lung slides stained by hematoxylin and eosin (H&E). Our method comprises four steps: 1) cascaded graph-based sparse PCA, 2) PCA binary hashing, 3) block-wise histograms, and 4) support vector machine (SVM) classification. In our proposed architecture, graph-based sparse PCA is employed to learn the filter banks of the multiple stages of a convolutional network. This is followed by PCA hashing and block histograms for indexing and pooling. The meaningful features extracted from this GS-PCA are then fed to an SVM classifier. We evaluate the performance of the proposed algorithm on H&E slides obtained from an inducible K-ras^G12D lung cancer mouse model using precision/recall rates, F_β-score, Tanimoto coefficient, and area under the curve (AUC) of the receiver operator characteristic (ROC) and show that our algorithm is efficient and provides improved detection accuracy compared to existing algorithms.

Single-cell transcriptome sequencing reveals heterogeneity of gastric cancer: progress and prospects

Gastric cancer is one of the most serious malignant tumor and threatens the health of people worldwide. Its heterogeneity leaves many clinical problems unsolved. To treat it effectively, we need to explore its heterogeneity. Single-cell transcriptome sequencing, or single-cell RNA sequencing (scRNA-seq), reveals the complex biological composition and molecular characteristics of gastric cancer at the level of individual cells, which provides a new perspective for understanding the heterogeneity of gastric cancer. In this review, we first introduce the current procedure of scRNA-seq, and discuss the advantages and limitations of scRNA-seq. We then elaborate on the research carried out with scRNA-seq in gastric cancer in recent years, and describe how it reveals cell heterogeneity, the tumor microenvironment, oncogenesis and metastasis, as well as drug response in to gastric cancer, to facilitate early diagnosis, individualized therapy, and prognosis evaluation.

Organoid models derived from patients with malignant phyllodes tumor of the breast

PURPOSE

Phyllodes tumor of the breast is a kind of rare neoplasm, which accounts for less than 1% of all breast tumors. Malignant phyllodes tumor (MPT) is the highest risk subtype of phyllodes tumor, and is characterized by the tendency of local recurrence and distant metastasis. The prediction of prognosis and the individual therapy for MPT is still challenging. It's urgent to develop a new reliable in vitro preclinical model in order to understand this disease better and to explore appropriate anticancer drugs for individual patients.

METHODS

Two surgically resected MPT specimens were processed for organoid establishment. MPT organoids were subsequently subjected to H&E staining, immunohistochemical analysis and drug screening, respectively.

RESULTS

We successfully established two organoid lines from different patients with MPT. The MPT organoids can well retain the histological features and capture the marker expression in original tumor tissues, including p63, vimentin, Bcl-2, CD34, c-Kit, and Ki-67, even after a long-term culture. The dose titration tests of eight typical chemotherapeutic drugs (paclitaxel, docetaxel, vincristine, doxorubicin, cisplatin, gemcitabine, cyclophosphamide, ifosfamide) on the two MPT organoid lines showed patient-specific drug responses and varying IC₅₀ values. Of all the drugs, doxorubicin and gemcitabine showed the best anti-tumor effect on the two organoid lines.

CONCLUSION

Organoids derived from MPT may be a novel preclinical model for testing personalized therapies for patients with MPT.

Valuing vicinity: Memory attention framework for context-based semantic segmentation in histopathology

The segmentation of histopathological whole slide images into tumourous and non-tumourous types of tissue is a challenging task that requires the consideration of both local and global spatial contexts to classify tumourous regions precisely. The identification of subtypes of tumour tissue complicates the issue as the sharpness of separation decreases and the pathologist's reasoning is even more guided by spatial context. However, the identification of detailed tissue types is crucial for providing personalized cancer therapies. Due to the high resolution of whole slide images, existing semantic segmentation methods, restricted to isolated image sections, are incapable of processing context information beyond. To take a step towards better context comprehension, we propose a patch neighbour attention mechanism to query the neighbouring tissue context from a patch embedding memory bank and infuse context embeddings into bottleneck hidden feature maps. Our memory attention framework (MAF) mimics a pathologist's annotation procedure - zooming out and considering surrounding tissue context. The framework can be integrated into any encoder-decoder segmentation method. We evaluate the MAF on two public breast cancer and liver cancer data sets and an internal kidney cancer data set using famous segmentation models (U-Net, DeeplabV3) and demonstrate the superiority over other context-integrating algorithms - achieving a substantial improvement of up to 17% on Dice score. The code is publicly available at https://github.com/tio-ikim/valuing-vicinity.

Chromosomal Instability in Genome Evolution: From Cancer to Macroevolution

The integrity of the genome is crucial for the survival of all living organisms. However, genomes need to adapt to survive certain pressures, and for this purpose use several mechanisms to diversify. Chromosomal instability (CIN) is one of the main mechanisms leading to the creation of genomic heterogeneity by altering the number of chromosomes and changing their structures. In this review, we will discuss the different chromosomal patterns and changes observed in speciation, in evolutional biology as well as during tumor progression. By nature, the human genome shows an induction of diversity during gametogenesis but as well during tumorigenesis that can conclude in drastic changes such as the whole genome doubling to more discrete changes as the complex chromosomal rearrangement chromothripsis. More importantly, changes observed during speciation are strikingly similar to the genomic evolution observed during tumor progression and resistance to therapy. The different origins of CIN will be treated as the importance of double-strand breaks (DSBs) or the consequences of micronuclei. We will also explain the mechanisms behind the controlled DSBs, and recombination of homologous chromosomes observed during meiosis, to explain how errors lead to similar patterns observed during tumorigenesis. Then, we will also list several diseases associated with CIN, resulting in fertility issues, miscarriage, rare genetic diseases, and cancer. Understanding better chromosomal instability as a whole is primordial for the understanding of mechanisms leading to tumor progression.

A subregion-based prediction model for local-regional recurrence risk in head and neck squamous cell carcinoma

BACKGROUND AND PURPOSE

Given that the intratumoral heterogeneity of head and neck squamous cell carcinoma may be related to the local control rate of radiotherapy, the aim of this study was to construct a subregion-based model that can predict the risk of local-regional recurrence, and to quantitatively assess the relative contribution of subregions.

MATERIALS AND METHODS

The CT images, PET images, dose images and GTVs of 228 patients with head and neck squamous cell carcinoma from four different institutions of the The Cancer Imaging Archive(TCIA) were included in the study. Using a supervoxel segmentation algorithm called maskSLIC to generate individual-level subregions. After extracting 1781 radiomics and 1767 dosiomics features from subregions, an attention-based multiple instance risk prediction model (MIR) was established. The GTV model was developed based on the whole tumour area and was used to compare the prediction performance with the MIR model. Furthermore, the MIR-Clinical model was constructed by integrating the MIR model with clinical factors. Subregional analysis was carried out through the Wilcoxon test to find the differential radiomic features between the highest and lowest weighted subregions.

RESULTS

Compared with the GTV model, the C-index of MIR model was significantly increased from 0.624 to 0.721(Wilcoxon test, p value< 0.0001). When MIR model was combined with clinical factors, the C-index was further increased to 0.766. Subregional analysis showed that for LR patients, the top three differential radiomic features between the highest and lowest weighted subregions were GLRLM_ShortRunHighGrayLevelEmphasis, GRLM_HghGrayLevelRunEmphasis and GLRLM_LongRunHighGrayLevelEmphasis.

CONCLUSION

This study developed a subregion-based model that can predict the risk of local-regional recurrence and quantitatively assess relevant subregions, which may provide technical support for the precision radiotherapy in head and neck squamous cell carcinoma.

Establishment of patient-derived tumor organoids to functionally inform treatment decisions in metastatic colorectal cancer

BACKGROUND

Metastatic colorectal cancer (mCRC) patients tend to have modest benefits from molecularly driven therapeutics. Patient-derived tumor organoids (PDTOs) represent an unmatched model to elucidate tumor resistance to therapy, due to their high capacity to resemble tumor characteristics.

MATERIALS AND METHODS

We used viable tumor tissue from two cohorts of patients with mCRC, naïve or refractory to treatment, respectively, for generating PDTOs. The derived models were subjected to a 6-day drug screening assay (DSA) with a comprehensive pipeline of chemotherapy and targeted drugs against almost all the actionable mCRC molecular drivers. For the second cohort DSA data were matched with those from PDTO genotyping.

RESULTS

A total of 40 PDTOs included in the two cohorts were derived from mCRC primary tumors or metastases. The first cohort included 31 PDTOs derived from patients treated in front line. For this cohort, DSA results were matched with patient responses. Moreover, RAS/BRAF mutational status was matched with DSA cetuximab response. Ten out of 12 (83.3%) RAS wild-type PDTOs responded to cetuximab, while all the mutant PDTOs, 8 out of 8 (100%), were resistant. For the second cohort (chemorefractory patients), we used part of tumor tissue for genotyping. Four out of nine DSA/genotyping data resulted applicable in the clinic. Two RAS-mutant mCRC patients have been treated with FOLFOX-bevacizumab and mitomycin-capecitabine in third line, respectively, based on DSA results, obtaining disease control. One patient was treated with nivolumab-second mitochondrial-derived activator of caspases mimetic (phase I trial) due to high tumor mutational burden at genotyping, experiencing stable disease. In one case, the presence of BRCA2 mutation correlated with DSA sensitivity to olaparib; however, the patient could not receive the therapy.

CONCLUSIONS

Using CRC as a model, we have designed and validated a clinically applicable methodology to potentially inform clinical decisions with functional data. Undoubtedly, further larger analyses are needed to improve methodology success rates and propose suitable treatment strategies for mCRC patients.

Spatial profiling of the microenvironment reveals low intratumoral heterogeneity and STK11-associated immune evasion in therapy-naïve lung adenocarcinomas

OBJECTIVE

Intratumoral heterogeneity was found to be a significant factor causing resistance to lung cancer therapies, including immune checkpoint blockade. Lesser is known about spatial heterogeneity of the tumor microenvironment (TME) and its association with genetic properties of the tumor, which is of particular interest in the therapy-naïve setting.

MATERIALS AND METHODS

We performed multi-region sampling (2-4 samples per tumor; total of 55 samples) from a cohort of 19 untreated stage IA-IIIB lung adenocarcinomas (n = 11 KRAS mutant, n = 1 ERBB2 mutant, n = 7 KRAS wildtype). For each sample the expression of 770 immunooncology-related genes was analyzed using the nCounter platform, while the mutational status was determined by hybrid capture-based next-generation sequencing (NGS) using a large panel covering more than 500 genes.

RESULTS

Global unsupervised analyses revealed clustering of the samples into two groups corresponding to a 'hot' or 'cold' immunologic tumor contexture based on the abundance of immune cell infiltrates. All analyzed specific immune cell signatures (ICsig) showed a significantly higher intertumoral than intratumoral heterogeneity (p < 0.02), as most of the analyzed cases (14/19) showed a very homogenous spatial immune cell profile. PD-L1 exhibited a significantly higher intertumoral than intratumoral heterogeneity (p = 1.03e-13). We found a specific association with 'cold' TME for STK11 (11/14, p < 0.07), but not KRAS, TP53, LRP1B, MTOR, U2AF1 co-mutations, and validated this finding using The Cancer Genome Atlas (TCGA) data.

CONCLUSION

Early-stage lung adenocarcinomas show considerable intertumoral, but limited intratumoral heterogeneity, which is clinically highly relevant as assessment before neoadjuvant treatment is based on small biopsies. STK11 mutations are specifically associated with a 'cold' TME, which could affect the efficacy of perioperative immunotherapy.

3D cancer models: One step closer to in vitro human studies

Cancer immunotherapy is the great breakthrough in cancer treatment as it displayed prolonged progression-free survival over conventional therapies, yet, to date, in only a minority of patients. In order to broad cancer immunotherapy clinical applicability some roadblocks need to be overcome, first among all the lack of preclinical models that faithfully depict the local tumor microenvironment (TME), which is known to dramatically affect disease onset, progression and response to therapy. In this review, we provide the reader with a detailed overview of current 3D models developed to mimick the complexity and the dynamics of the TME, with a focus on understanding why the TME is a major target in anticancer therapy. We highlight the advantages and translational potentials of tumor spheroids, organoids and immune Tumor-on-a-Chip models in disease modeling and therapeutic response, while outlining pending challenges and limitations. Thinking forward, we focus on the possibility to integrate the know-hows of micro-engineers, cancer immunologists, pharmaceutical researchers and bioinformaticians to meet the needs of cancer researchers and clinicians interested in using these platforms with high fidelity for patient-tailored disease modeling and drug discovery.

Immunomodulatory effect of locoregional therapy in the tumor microenvironment

Cancer immunotherapy appears to be a promising treatment option; however, only a subset of patients with cancer responds favorably to treatment. Locoregional therapy initiates a local antitumor immune response by disrupting immunosuppressive components, releasing immunostimulatory damage-associated molecular patterns, recruiting immune effectors, and remodeling the tumor microenvironment. Many studies have shown that locoregional therapy can produce specific antitumor immunity alone; nevertheless, the effect is relatively weak and transient. Furthermore, increasing research efforts have explored the potential synergy between locoregional therapy and immunotherapy to enhance the long-term systemic antitumor immune effect and improve survival. Therefore, further research is needed into the immunomodulatory effects of locoregional therapy and immunotherapy to augment antitumor effects. This review article summarizes the key components of the tumor microenvironment, discusses the immunomodulatory role of locoregional therapy in the tumor microenvironment, and emphasizes the therapeutic potential of locoregional therapy in combination with immune checkpoint inhibitors.

Dissecting tumor lymphocyte infiltration to predict benefit from immune-checkpoint inhibitors in metastatic colorectal cancer: lessons from the AtezoT RIBE study

BACKGROUND

Tumor immune cells influence the efficacy of immune-checkpoint inhibitors (ICIs) and many efforts aim at identifying features of tumor immune microenvironment able to predict benefit from ICIs in proficient mismatch repair (pMMR)/microsatellite stable (MSS) metastatic colorectal cancer (mCRC).

METHODS

We characterized tumor immune cell infiltrate, by assessing tumor-infiltrating lymphocytes (TILs), Immunoscore, Immunoscore-IC, and programmed death ligand-1 (PD-L1) expression in tumor samples of patients with mCRC enrolled in the AtezoTRIBE study, a phase II randomized trial comparing FOLFOXIRI/bevacizumab/atezolizumab to FOLFOXIRI/bevacizumab, with the aim of evaluating the prognostic and predictive value of these features.

RESULTS

Out of 218 patients enrolled, 181 (83%), 77 (35%), 157 (72%) and 162 (74%) specimens were successfully tested for TILs, Immunoscore, Immunoscore-IC and PD-L1 expression, respectively, and 69 (38%), 45 (58%), 50 (32%) and 21 (13%) tumors were classified as TILs-high, Immunoscore-high, Immunoscore-IC-high and PD-L1-high, respectively. A poor agreement was observed between TILs and Immunoscore or Immunoscore-IC (K of Cohen <0.20). In the pMMR population, longer progression-free survival (PFS) was reported for Immunoscore-high and Immunoscore-IC-high groups compared with Immunoscore-low (16.4 vs 12.2 months; HR: 0.55, 95% CI: 0.30 to 0.99; p=0.049) and Immunoscore-IC-low (14.8 vs 11.5 months; HR: 0.55, 95% CI: 0.35 to 0.85; p=0.007), respectively, with a significant interaction effect between treatment arms and Immunoscore-IC (p for interaction: 0.006) and a trend for Immunoscore (p for interaction: 0.13). No PFS difference was shown according to TILs and PD-L1 expression. Consistent results were reported in the overall population.

CONCLUSIONS

The digital evaluation of tumor immune cell infiltrate by means of Immunoscore-IC or Immunoscore identifies the subset of patients with pMMR mCRC achieving more benefit from the addition of the anti-PD-L1 to the upfront treatment. Immunoscore-IC stands as the most promising predictor of benefit from ICIs.

Tumor-associated macrophage-derived GDNF promotes gastric cancer liver metastasis via a GFRA1-modulated autophagy flux

PURPOSE

Liver metastasis, a lethal malignancy of gastric cancer (GC) patients, execrably impairs their prognosis. As yet, however, few studies have been designed to identify the driving molecules during its formation, except screening evidence pausing before their functions or mechanisms. Here, we aimed to survey a key driving event within the invasive margin of liver metastases.

METHODS

A metastatic GC tissue microarray was used for exploring malignant events during liver-metastasis formation, followed by assessing the expression patterns of glial cell-derived neurotrophic factor (GDNF) and GDNF family receptor alpha 1 (GFRA1). Their oncogenic functions were determined by both loss- and gain-of-function studies in vitro and in vivo, and validated by rescue experiments. Multiple cell biological studies were performed to identify the underlying mechanisms.

RESULTS

In the invasive margin, GFRA1 was identified as a pivotal molecule involved in cellular survival during liver metastasis formation, and we found that its oncogenic role depends on tumor associated macrophage (TAM)-derived GDNF. In addition, we found that the GDNF-GFRA1 axis protects tumor cells from apoptosis under metabolic stress via regulating lysosomal functions and autophagy flux, and participates in the regulation of cytosolic calcium ion signalling in a RET-independent and non-canonical way.

CONCLUSION

From our data we conclude that TAMs, homing around metastatic nests, induce the autophagy flux of GC cells and promote the development of liver metastasis via GDNF-GFRA1 signalling. This is expected to improve the comprehension of metastatic pathogenesis and to provide a novel direction of research and translational strategies for the treatment of metastatic GC patients.

Systematic pan-cancer analysis identifies SLC35C1 as an immunological and prognostic biomarker

GDP-amylose transporter protein 1 (SLC35C1) plays an important role in many types of cancer. Therefore, it is clinically important to further investigate the expression profile of SLC35C1 in human tumors to provide new molecular clues for the pathogenesis of glioma. In this study, we performed a comprehensive pan-cancer analysis of SLC35C1 using a series of bioinformatics approaches and validated its differential tissue expression and biological function. The results showed that SLC35C1 was aberrantly expressed in different types of tumors and significantly correlated with overall survival (OS) and progression-free interval (PFI). More importantly, the expression level of SLC35C1 was closely correlated with Tumor Microenvironment (TME), immune infiltration and immune-related genes. In addition, we found that SLC35C1 expression was also closely related to Tumor Mutation Burden (TMB), Microsatellite Instability (MSI) and antitumor drug sensitivity in various cancer types. Functional bioinformatics analysis indicated that SLC35C1 may be involved in multiple signaling pathways and biological processes in glioma. Based on SLC35C1 expression, a risk factor model was found to predict OS of glioma. In addition, in vitro experiments showed that SLC35C1 knockdown significantly inhibited the proliferation, migration and invasive ability of glioma cells, while SLC35C1 overexpression promoted proliferation, migration, invasion and colony formation of glioma cells. Finally, quantitative real-time PCR confirmed that SLC35C1 was highly expressed in gliomas.

State-dependent evolutionary models reveal modes of solid tumour growth

Spatial properties of tumour growth have profound implications for cancer progression, therapeutic resistance and metastasis. Yet, how spatial position governs tumour cell division remains difficult to evaluate in clinical tumours. Here, we demonstrate that faster division on the tumour periphery leaves characteristic genetic patterns, which become evident when a phylogenetic tree is reconstructed from spatially sampled cells. Namely, rapidly dividing peripheral lineages branch more extensively and acquire more mutations than slower-dividing centre lineages. We develop a Bayesian state-dependent evolutionary phylodynamic model (SDevo) that quantifies these patterns to infer the differential division rates between peripheral and central cells. We demonstrate that this approach accurately infers spatially varying birth rates of simulated tumours across a range of growth conditions and sampling strategies. We then show that SDevo outperforms state-of-the-art, non-cancer multi-state phylodynamic methods that ignore differential sequence evolution. Finally, we apply SDevo to single-time-point, multi-region sequencing data from clinical hepatocellular carcinomas and find evidence of a three- to six-times-higher division rate on the tumour edge. With the increasing availability of high-resolution, multi-region sequencing, we anticipate that SDevo will be useful in interrogating spatial growth restrictions and could be extended to model non-spatial factors that influence tumour progression.

CD142 Identifies Neoplastic Desmoid Tumor Cells, Uncovering Interactions Between Neoplastic and Stromal Cells That Drive Proliferation

The interaction between neoplastic and stromal cells within a tumor mass plays an important role in cancer biology. However, it is challenging to distinguish between tumor and stromal cells in mesenchymal tumors because lineage-specific cell surface markers typically used in other cancers do not distinguish between the different cell subpopulations. Desmoid tumors consist of mesenchymal fibroblast-like cells driven by mutations stabilizing beta-catenin. Here we aimed to identify surface markers that can distinguish mutant cells from stromal cells to study tumor-stroma interactions. We analyzed colonies derived from single cells from human desmoid tumors using a high-throughput surface antigen screen, to characterize the mutant and nonmutant cells. We found that CD142 is highly expressed by the mutant cell populations and correlates with beta-catenin activity. CD142-based cell sorting isolated the mutant population from heterogeneous samples, including one where no mutation was previously detected by traditional Sanger sequencing. We then studied the secretome of mutant and nonmutant fibroblastic cells. PTX3 is one stroma-derived secreted factor that increases mutant cell proliferation via STAT6 activation. These data demonstrate a sensitive method to quantify and distinguish neoplastic from stromal cells in mesenchymal tumors. It identifies proteins secreted by nonmutant cells that regulate mutant cell proliferation that could be therapeutically.

Significance

Distinguishing between neoplastic (tumor) and non-neoplastic (stromal) cells within mesenchymal tumors is particularly challenging, because lineage-specific cell surface markers typically used in other cancers do not differentiate between the different cell subpopulations. Here, we developed a strategy combining clonal expansion with surface proteome profiling to identify markers for quantifying and isolating mutant and nonmutant cell subpopulations in desmoid tumors, and to study their interactions via soluble factors.

Microfluidic Droplet-Assisted Fabrication of Vessel-Supported Tumors for Preclinical Drug Discovery

High-fidelity in vitro tumor models are important for preclinical drug discovery processes. Currently, the most commonly used model for in vitro drug testing remains the two-dimensional (2D) cell monolayer. However, the natural in vivo tumor microenvironment (TME) consists of extracellular matrix (ECM), supporting stromal cells and vasculature. They not only participate in the progression of tumors but also hinder drug delivery and effectiveness on tumor cells. Here, we report an integrated engineering system to generate vessel-supported tumors for preclinical drug screening. First, gelatin-methacryloyl (GelMA) hydrogel was selected to mimic tumor extracellular matrix (ECM). HCT-116 tumor cells were encapsulated into individual micro-GelMA beads with microfluidic droplet technique to mimic tumor-ECM interactions in vitro. Then, normal human lung fibroblasts were mingled with tumor cells to imitate the tumor-stromal interaction. The tumor cells and fibroblasts reconstituted in the individual GelMA microbead and formed a biomimetic heterotypic tumor model with a core-shell structure. Next, the cell-laden beads were consociated into a functional on-chip vessel network platform to restore the tumor-tumor microenvironment (TME) interaction. Afterward, the anticancer drug paclitaxel was tested on the individual and vessel-supported tumor models. It was demonstrated that the blood vessel-associated TME conferred significant additional drug resistance in the drug screening experiment. The reported system is expected to enable the large-scale fabrication of vessel-supported heterotypic tumor models of various cellular compositions. It is believed to be promising for the large-scale fabrication of biomimetic in vitro tumor models and may be valuable for improving the efficiency of preclinical drug discovery processes.

Comprehensive pan-cancer analysis of STAT3 as a prognostic and immunological biomarker

Numerous studies have indicated that STAT3 plays a key role in promoting oncogenesis and it is considered a potential therapeutic target for cancer treatment; however, there are no reports on STAT3 using pan-cancer analysis. Therefore, it is important to investigate the role of STAT3 in different types of tumors using pan-cancer analysis. In the present study, we used multiple databases to comprehensively analyze the relationship between STAT3 expression and prognosis, different stages of patients with cancer, investigate the clinical value of STAT3 in predicting prognosis, and the relationship between STAT3 genetic alteration and prognosis, drug sensitivity, and STAT3 expression, to determine whether STAT3 participates in tumor immunity, to provide a rationale for STAT3 as a treatment target for a broad-spectrum malignancies. Our results indicate that STAT3 can serve as a prognostic, sensitivity prediction biomarker and a target for immunotherapy, which has been of great value for pan-cancer treatment. Overall, we found that STAT3 significantly predicted cancer prognosis, drug resistance, and immunotherapy, providing a rationale for further experimental studies.

Mesoporous nanodrug delivery system: a powerful tool for a new paradigm of remodeling of the tumor microenvironment

Tumor microenvironment (TME) plays an important role in tumor progression, metastasis and therapy resistance. Remodeling the TME has recently been deemed an attractive tumor therapeutic strategy. Due to its complexity and heterogeneity, remodeling the TME still faces great challenges. With the great advantage of drug loading ability, tumor accumulation, multifactor controllability, and persistent guest molecule release ability, mesoporous nanodrug delivery systems (MNDDSs) have been widely used as effective antitumor drug delivery tools as well as remolding TME. This review summarizes the components and characteristics of the TME, as well as the crosstalk between the TME and cancer cells and focuses on the important role of drug delivery strategies based on MNDDSs in targeted remodeling TME metabolic and synergistic anticancer therapy.

Targeted Fusogenic Liposomes for Effective Tumor Delivery and Penetration of Lipophilic Cargoes

Nanoparticle-based drug delivery has been widely used for effective anticancer treatment. However, a key challenge restricting the efficacy of nanotherapeutics is limited tissue penetration within solid tumors. Here, we report a targeted fusogenic liposome (TFL) that can selectively deliver lipophilic cargo to the plasma membranes of tumor cells. TFL is prepared by directly attaching tumor-targeting peptides to the surface of FL instead of the cationic moieties. The lipophilic cargo loaded in the membrane of TFL is transferred to the plasma membranes of tumor cells and subsequently packaged in the extracellular vesicles (EVs) released by the cells. Systemically administered TFL accumulates in the perivascular region of tumors, where the lipophilic cargo is unloaded to the tumor cell membranes and distributed autonomously throughout the tumor tissue via extracellular vesicle-mediated intercellular transfer. When loaded with a lipophilic pro-apoptotic drug, thapsigargin (Tg), TFL significantly inhibits tumor growth in a mouse colorectal cancer model. Furthermore, the combination treatment with TFL (Tg) potentiates the antitumor efficacy of FDA-approved liposomal doxorubicin, whose therapeutic effect is limited to perivascular regions without significant toxicity.

Biomaterial-based platforms for modulating immune components against cancer and cancer stem cells

Immunotherapy involves the therapeutic alteration of the patient's immune system to identify, target, and eliminate cancer cells. Dendritic cells, macrophages, myeloid-derived suppressor cells, and regulatory T cells make up the tumor microenvironment. In cancer, these immune components (in association with some non-immune cell populations like cancer-associated fibroblasts) are directly altered at a cellular level. By dominating immune cells with molecular cross-talk, cancer cells can proliferate unchecked. Current clinical immunotherapy strategies are limited to conventional adoptive cell therapy or immune checkpoint blockade. Targeting and modulating key immune components presents an effective opportunity. Immunostimulatory drugs are a research hotspot, but their poor pharmacokinetics, low tumor accumulation, and non-specific systemic toxicity limit their use. This review describes the cutting-edge research undertaken in the field of nanotechnology and material science to develop biomaterials-based platforms as effective immunotherapeutics. Various biomaterial types (polymer-based, lipid-based, carbon-based, cell-derived, etc.) and functionalization methodologies for modulating tumor-associated immune/non-immune cells are explored. Additionally, emphasis has been laid on discussing how these platforms can be used against cancer stem cells, a fundamental contributor to chemoresistance, tumor relapse/metastasis, and failure of immunotherapy. Overall, this comprehensive review strives to provide up-to-date information to an audience working at the juncture of biomaterials and cancer immunotherapy. STATEMENT OF SIGNIFICANCE: Cancer immunotherapy possesses incredible potential and has successfully transitioned into a clinically lucrative alternative to conventional anti-cancer therapies. With new immunotherapeutics getting rapid clinical approval, fundamental problems associated with the dynamic nature of the immune system (like limited clinical response rates and autoimmunity-related adverse effects) have remained unanswered. In this context, treatment approaches that focus on modulating the compromised immune components within the tumor microenvironment have garnered significant attention amongst the scientific community. This review aims to provide a critical discussion on how various biomaterials (polymer-based, lipid-based, carbon-based, cell-derived, etc.) can be employed along with immunostimulatory agents to design innovative platforms for selective immunotherapy directed against cancer and cancer stem cells.

Geographically weighted linear combination test for gene-set analysis of a continuous spatial phenotype as applied to intratumor heterogeneity

Background: The impact of gene-sets on a spatial phenotype is not necessarily uniform across different locations of cancer tissue. This study introduces a computational platform, GWLCT, for combining gene set analysis with spatial data modeling to provide a new statistical test for location-specific association of phenotypes and molecular pathways in spatial single-cell RNA-seq data collected from an input tumor sample.

Methods: The main advantage of GWLCT consists of an analysis beyond global significance, allowing the association between the gene-set and the phenotype to vary across the tumor space. At each location, the most significant linear combination is found using a geographically weighted shrunken covariance matrix and kernel function. Whether a fixed or adaptive bandwidth is determined based on a cross-validation cross procedure. Our proposed method is compared to the global version of linear combination test (LCT), bulk and random-forest based gene-set enrichment analyses using data created by the Visium Spatial Gene Expression technique on an invasive breast cancer tissue sample, as well as 144 different simulation scenarios.

Results: In an illustrative example, the new geographically weighted linear combination test, GWLCT, identifies the cancer hallmark gene-sets that are significantly associated at each location with the five spatially continuous phenotypic contexts in the tumors defined by different well-known markers of cancer-associated fibroblasts. Scan statistics revealed clustering in the number of significant gene-sets. A spatial heatmap of combined significance over all selected gene-sets is also produced. Extensive simulation studies demonstrate that our proposed approach outperforms other methods in the considered scenarios, especially when the spatial association increases.

Conclusion: Our proposed approach considers the spatial covariance of gene expression to detect the most significant gene-sets affecting a continuous phenotype. It reveals spatially detailed information in tissue space and can thus play a key role in understanding the contextual heterogeneity of cancer cells.

Perfusion Air Culture of Precision-Cut Tumor Slices: An Ex Vivo System to Evaluate Individual Drug Response under Controlled Culture Conditions

Precision-cut tumor slices (PCTS) maintain tissue heterogeneity concerning different cell types and preserve the tumor microenvironment (TME). Typically, PCTS are cultured statically on a filter support at an air-liquid interface, which gives rise to intra-slice gradients during culture. To overcome this problem, we developed a perfusion air culture (PAC) system that can provide a continuous and controlled oxygen medium, and drug supply. This makes it an adaptable ex vivo system for evaluating drug responses in a tissue-specific microenvironment. PCTS from mouse xenografts (MCF-7, H1437) and primary human ovarian tumors (primary OV) cultured in the PAC system maintained the morphology, proliferation, and TME for more than 7 days, and no intra-slice gradients were observed. Cultured PCTS were analyzed for DNA damage, apoptosis, and transcriptional biomarkers for the cellular stress response. For the primary OV slices, cisplatin treatment induced a diverse increase in the cleavage of caspase-3 and PD-L1 expression, indicating a heterogeneous response to drug treatment between patients. Immune cells were preserved throughout the culturing period, indicating that immune therapy can be analyzed. The novel PAC system is suitable for assessing individual drug responses and can thus be used as a preclinical model to predict in vivo therapy responses.

Cancer-associated fibroblasts promote tumor cell growth via miR-493-5p in intrahepatic cholangiocarcinoma

The association between tumor microenvironment (TME) and cancer-associated fibroblasts (CAFs) in intrahepatic cholangiocarcinoma (ICC) progression is poorly understood. This study aimed to reveal whether specific microRNAs (miRNAs) in extracellular vesicles (EVs) derived from CAFs were involved in ICC progression. Conditioned medium (CM) and EVs in the CM of CAFs and normal fibroblasts (NFs) derived from ICC specimens were used to investigate the effects on tumor cell lines. miRNA microarray assay was used to examine the miRNAs of EVs derived from CAFs and NFs in ICC, and the effects of miR-493-5p on tumor cell lines were examined. Additionally, databases were used to identify miR-493-5p targets, and the relationship between prognosis of ICC patients and cocaine- and amphetamine-regulated transcript propeptide (CARTPT), one of the targets of miR-493-5p, expression in ICC tissues was retrospectively analyzed. Compared with NF-derived CM and EVs, CAF-derived CM and EVs promoted cell lines in proliferation, scratch, migration, and invasion assays. miRNA microarray analysis revealed that miR-493-5p was significantly increased in CAF-derived EVs compared to NF-derived EVs. Tumor cell lines transfected with miR-493-5p were promoted in proliferation and scratch assays. Immunohistochemical staining was performed on 76 ICC specimens; both overall and recurrence-free survival rates were significantly worse in the CARTPT-negative group. Univariate and multivariate analyses showed that low CARTPT expression was an independent poor prognostic factor for overall and recurrence-free survival. Overall, our data suggest that CAFs in the ICC TME suppress CARTPT in tumor cells and promote tumor cells via miR-493-5p in EVs.

Integrative characterisation of secreted factors involved in intercellular communication between prostate epithelial or cancer cells and fibroblasts

Reciprocal interactions between prostate cancer cells and carcinoma-associated fibroblasts (CAFs) mediate cancer development and progression; however, our understanding of the signalling pathways mediating these cellular interactions remains incomplete. To address this, we defined secretome changes upon co-culture of prostate epithelial or cancer cells with fibroblasts that mimic bi-directional communication in tumours. Using antibody arrays, we profiled conditioned media from mono- and co-cultures of prostate fibroblasts, epithelial and cancer cells, identifying secreted proteins that are upregulated in co-culture compared to mono-culture. Six of these (CXCL10, CXCL16, CXCL6, FST, PDGFAA, IL-17B) were functionally screened by siRNA knockdown in prostate cancer cell/fibroblast co-cultures, revealing a key role for follistatin (FST), a secreted glycoprotein that binds and bioneutralises specific members of the TGF-β superfamily, including activin A. Expression of FST by both cell types was required for the fibroblasts to enhance prostate cancer cell proliferation and migration, whereas FST knockdown in co-culture grafts decreased tumour growth in mouse xenografts. This study highlights the complexity of prostate cancer cell-fibroblast communication, demonstrates that co-culture secretomes cannot be predicted from individual cultures, and identifies FST as a tumour-microenvironment-derived secreted factor that represents a candidate therapeutic target.

The role of ubiquitin pathway-mediated regulation of immune checkpoints in cancer immunotherapy

With the continuous cognition of the relationship between tumor cells and tumor immune microenvironment, immunotherapy based on the immune checkpoint blockade has achieved great breakthroughs, led to improved clinical outcomes, and prolonged survival for cancer patients in recent years. Nevertheless, the de novo or acquired resistance to immunotherapy has greatly counteracted the efficacy, leading to a 20%-40% overall response rate. Thus, further in-depth understanding of the regulation of the tumor microenvironment and antitumor immunity is urgently warranted. Ubiquitination-mediated protein degradation plays vital roles in protein stabilization, activation, and dynamics as well as in cellular homeostasis modulation. The dysregulated ubiquitination and deubiquitination are closely related to the changes in physiological and pathological processes, which subsequently result in a variety of diseases including cancer. In this review, the authors first summarize the current knowledge about the involvement of the ubiquitin-proteasome system in tumor development with the ubiquitin conjugation-regulated stability of p53, phosphatase and tensin homolog, and Myc protein as examples, then dissect the potential implications of ubiquitination-mediated immune checkpoints degradation in tumor microenvironment and immune responses, and finally discuss the effects of therapeutically targeting the ubiquitin-proteasome pathway on immunotherapy, with the goal of providing deep insights into the exploitation of more precise and effective combinational therapy against cancer.

Ultrasound-targeted microbubble destruction remodels tumour microenvironment to improve immunotherapeutic effect

Cancer immunotherapy (CIT) has gained increasing attention and made promising progress in recent years, especially immune checkpoint inhibitors such as antibodies blocking programmed cell death 1/programmed cell death ligand 1 (PD-1/PD-L1) and cytotoxic T lymphocyte-associated protein 4 (CTLA-4). However, its therapeutic efficacy is only 10-30% in solid tumours and treatment sensitivity needs to be improved. The complex tissue environment in which cancers originate is known as the tumour microenvironment (TME) and the complicated and dynamic TME is correlated with the efficacy of immunotherapy. Ultrasound-targeted microbubble destruction (UTMD) is an emerging technology that integrates diagnosis and therapy, which has garnered much traction due to non-invasive, targeted drug delivery and gene transfection characteristics. UTMD has also been studied to remodel TME and improve the efficacy of CIT. In this review, we analyse the effects of UTMD on various components of TME, including CD8⁺ T cells, tumour-infiltrating myeloid cells, regulatory T cells, natural killer cells and tumour vasculature. Moreover, UTMD enhances the permeability of the blood-brain barrier to facilitate drug delivery, thus improving CIT efficacy in vivo animal experiments. Based on this, we highlight the potential of immunotherapy against various cancer species and the clinical application prospects of UTMD.

Influences of intratumoral heterogeneity on assessment of tumor microenvironment in esophageal squamous cell carcinoma

The intratumoral heterogeneity (ITH) of the tumor microenvironment (TME) has yet to be addressed in esophageal squamous cell carcinoma (ESCC). Here, we studied the ITH of CD8 and PD-L1 status in ESCC, and examined the potential of the tumor surface for representing the TME. In total, 67 surgically resected clinical Stage II ESCC specimens were analyzed. The CD8-cell density, PD-L1 tumor proportion score (TPS), and combined positive score (CPS) were calculated in three (superficial, middle, and deep) areas of each specimen. ITH was quantified by distance-standardized coefficient variations of the three values. The CD8 and PD-L1 status of each area was dichotomized and tumor-surface capabilities for predicting the entire tumor status were estimated. Variables were compared according to the presence of neoadjuvant chemotherapy (NAC). The ITH, especially PD-L1 heterogeneity, differed markedly among specimens. The concordance rates of CD8 and PD-L1 (CPS and TPS) status among the three different areas were 71.6%, 74.6%, and 73.1%, respectively. The sensitivity and the specificity of the tumor surface for predicting the CD8 status of the whole tumor were high, especially in the NAC- group (both 1.0). The tumor surface also showed high capabilities for representing the whole PD-L1 status, while yielding moderate positive predictive values (0.70). The ITH degrees and predictive capabilities did not differ according to NAC. Taken together, the ITH of CD8 and PD-L1 differed among ESCC specimens, while not being markedly affected by NAC. The use of a biopsy specimen from the tumor surface might be feasible for TME evaluation.

Comprehensive Pan-Cancer Analysis of MTF2 Effects on Human Tumors

Understanding oncogenic processes and underlying mechanisms to advance research into human tumors is critical for effective treatment. Studies have shown that Metal regulatory transcription factor 2（MTF2) drives malignant progression in liver cancer and glioma. However, no systematic pan-cancer analysis of MTF2 has been performed. Here, we use University of California Santa Cruz, Cancer Genome Atlas , Genotype-Tissue Expression data, Tumor Immune Estimation Resource, and Clinical Proteomic Tumor Analysis Consortium bioinformatics tools to explore differential expression of MTF2 across different tumor types. MTF2 was found to be highly expressed in the cancer lines that were available through the respective databases included in the study, and overexpression of MTF2 may lead to a poor prognosis in tumor patients such as glioblastoma multiforme, brain lower grade glioma, KIPAN, LIHC, adrenocortical carcinoma, etc. We also validated MTF2 mutations in cancer, compared MTF2 methylation levels in normal and primary tumor tissues, analyzed the association of MTF2 with the immune microenvironment, and validated the functional role of MTF2 in glioma U87 and U251 and breast cancer MDA-MB-231 cell lines by cytometry. This also indicates that MTF2 has a promising application prospect in cancer treatment.

Improvements and challenges of tissue preparation for spatial transcriptome analysis of skull base tumors

BACKGROUND

Spatial transcriptome (ST) provides molecular profiles of tumor cells at the spatial level, which brings new progress to the research of tumors and the tumor microenvironment. This study summarizes the experiences and lessons learned in the spatial section preparation of two different pathological types of nose and skull base tumors at our institution, with the aim of offering guidelines to researchers to avoid wasting precious samples and provide a basis for the application of ST in clinical practice.

METHODS

Frozen tissue blocks from patients with squamous cell carcinoma and adenocarcinoma of the nose and skull base diagnosed at our institution were prepared. The effects of different procedures and pathological tissue types on slide quality were explored and evaluated using RNA integrity number (RIN) and HE scores as criteria. The effects of different RIN values on ST sequencing data were explored.

RESULTS

A total of 43 samples were obtained from 26 patients, including 22 with squamous carcinomas and 21 with adenocarcinomas. Thirteen samples with satisfactory RNA quality control and good histological morphology were sequenced for ST. Sample isolation time <15 min and abandonment of snap-frozen isopentane significantly improved RNA quality (p = 0.004, p < 0.0001) and histomorphological integrity (p = 0.02, p = 0.02). Selection of a suitable tissue RNA extraction kit was critical for RNA quality (p < 0.0001). No difference between 6 ≤ RIN <7 and RIN >7 in ST sequencing results was found, indicating that RIN ≥6 can be used as a criterion for qualified RNA quality control. Therefore, fresh tissues washed as soon as possible with cold PBS and then dried using OCT for snap freezing are currently the best method for preparing spatial sections of nose and skull base tumor tissues of different pathological types.

CONCLUSION

This study is the first to investigate the feasibility of applying ST to different pathological types of nose and skull base tumors and to demonstrate the widespread application of ST in tumors. Rational optimization of spatial slide preparation procedures and exploration of individualized pre-sequencing protocols are used as the first stage to ensure the quality of spatial sequencing and lay the foundation for subsequent spatial analysis.

Correlation of 18F-FDG PET/CT metabolic parameters with the expression of immune biomarkers in the tumour microenvironment in lung adenocarcinoma

AIM

To explore the association between metabolic parameters evaluated by integrated 2-[¹⁸F]-fluoro-2-deoxy-d-glucose (FDG) positron-emission tomography (PET)/computed tomography (CT) and the expression of immune biomarkers in the tumour microenvironment in lung adenocarcinoma.

MATERIALS AND METHODS

This study included 134 patients. Metabolic parameters were obtained by PET/CT. Immunohistochemistry analysis was used for FOXP3-TILs (transcription factor forkhead box protein 3 tumour-infiltrating lymphocytes), CD8-TILs, CD4-TILs, CD68-TAMs (tumour-associated macrophages) and galectin-1 (Gal-1) tumour expression.

RESULTS

There were significant positive associations between FDG PET metabolic parameters and the median percentage of immune reactive areas (IRA%) covered by FOXP3-TILs and CD68-TAMs. Negative associations with the median IRA% covered by CD4-TILs and CD8-TILs were observed: maximal standardised uptake value (SUV_max), metabolic tumour volume (MTV), total lesion glycolysis (TLG), and IRA% for FOXP3-TILs (rho = 0.437, 0.400, 0.414; p<0.0001 for all parameters); SUV_max, MTV, TLG, and IRA% for CD68-TAMs (rho = 0.356, 0.355, 0.354; p<0.0001 for all parameters); SUV_max, MTV, TLG, and IRA% for CD4-TILs (rho = -0.164, -0.190, -0.191; p=0.059, 0.028, 0.027, respectively); SUV_max, MTV, TLG, and IRA% for CD8-TILs (rho = -0.305, -0.316, -0.322; p<0.0001 for all parameters). There were significant positive associations between tumour Gal-1 expression and the median IRA% covered by FOXP3-TILs and CD68-TAMs (rho = 0.379; p<0.0001; rho = 0.370; p<0.0001, respectively), and a significant negative association with the median IRA% covered by CD8-TILs (rho = -0.347; p<0.0001) was observed. Tumour stage (p=0.008), Gal-1 expression (p=0.008), and median IRA% covered by CD8-TILs (p=0.054) were independent risk factors for overall survival.

CONCLUSION

FDG PET may facilitate a comprehensive evaluation of the tumour microenvironment and predict response to immunotherapy.

Deep learning in digital pathology for personalized treatment plans of cancer patients

Over the past decade, many new cancer treatments have been developed and made available to patients. However, in most cases, these treatments only benefit a specific subgroup of patients, making the selection of treatment for a specific patient an essential but challenging task for oncologists. Although some biomarkers were found to associate with treatment response, manual assessment is time-consuming and subjective. With the rapid developments and expanded implementation of artificial intelligence (AI) in digital pathology, many biomarkers can be quantified automatically from histopathology images. This approach allows for a more efficient and objective assessment of biomarkers, aiding oncologists in formulating personalized treatment plans for cancer patients. This review presents an overview and summary of the recent studies on biomarker quantification and treatment response prediction using hematoxylin-eosin (H&E) stained pathology images. These studies have shown that an AI-based digital pathology approach can be practical and will become increasingly important in improving the selection of cancer treatments for patients.

Recent trends in emerging strategies for ferroptosis-based cancer therapy

Ferroptosis, an iron-dependent mode of regulated cell death, is induced by lipid peroxidation, whose occurrence and execution are primarily controlled by metabolism of iron, lipids, amino acids and glutathione. In recent years, the fast-growing studies of ferroptosis in cancer have promoted its application in cancer therapy. So, this review focuses on the feasibility and characteristics of initiating ferroptosis for cancer therapy, as well as the main mechanism of ferroptosis. And various emerging strategies of cancer therapy based on ferroptosis are then highlighted to describe their design, mechanism of action, and anticancer applications. In addition ferroptosis in diverse cancer types is summarized, some considerations for the research of various preparations that can cause ferroptosis are introduced, and this emerging field is discussed in terms of its challenges and future development directions.

The Characteristics of Tumor Microenvironment Predict Survival and Response to Immunotherapy in Adrenocortical Carcinomas

Increasing evidence confirms that tumor microenvironment (TME) can influence tumor progression and treatment, but TME is still understudied in adrenocortical carcinoma (ACC). In this study, we first scored TME using the xCell algorithm, then defined genes associated with TME, and then used consensus unsupervised clustering analysis to construct TME-related subtypes. Meanwhile, weighted gene co-expression network analysis was used to identify modules correlated with TME-related subtypes. Ultimately, the LASSO-Cox approach was used to establish a TME-related signature. The results showed that TME-related scores in ACC may not correlate with clinical features but do promote a better overall survival. Patients were classified into two TME-related subtypes. Subtype 2 had more immune signaling features, higher expression of immune checkpoints and MHC molecules, no CTNNB1 mutations, higher infiltration of macrophages and endothelial cells, lower tumor immune dysfunction and exclusion scores, and higher immunophenoscore, suggesting that subtype 2 may be more sensitive to immunotherapy. 231 modular genes highly relevant to TME-related subtypes were identified, and a 7-gene TME-related signature that independently predicted patient prognosis was established. Our study revealed an integrated role of TME in ACC and helped to identify those patients who really responded to immunotherapy, while providing new strategies on risk management and prognosis prediction.

Radiomics insight into the neurodegenerative "hot" brain: A narrative review from the nuclear medicine perspective

The application of radiomics for non-oncologic diseases is currently emerging. Despite its relative infancy state, the evidence highlights the potential of radiomics approaches to serve as neuroimaging biomarkers in the field of the neurodegenerative brain. This systematic review presents the last progress and potential application of radiomics in the field of neurodegenerative nuclear imaging applied to positron-emission tomography (PET) and single-photon emission computed tomography (SPECT) by focusing mainly on the two most common neurodegenerative disorders, Alzheimer's (AD) and Parkinson's disease (PD). A comprehensive review of the current literature was performed using the PubMed and Web of Science databases up to November 2022. The final collection of eighteen relevant publications was grouped as AD-related and PD-related. The main efforts in the field of AD dealt with radiomics-based early diagnosis of preclinical AD and the prediction of MCI to AD conversion, meanwhile, in the setting of PD, the radiomics techniques have been used in the attempt to improve the assessment of PD diagnosis, the differential diagnosis between PD and other parkinsonism, severity assessment, and outcome prediction. Although limited evidence with relatively small cohort studies, it seems that radiomics-based analysis using nuclear medicine tools, mainly [18F]Fluorodeoxyglucose (FDG) and β-amyloid (Aβ) PET, and dopamine transporter (DAT) SPECT, can be used for computer-aided diagnoses in AD-continuum and parkinsonian disorders. Combining nuclear radiomics analysis with clinical factors and introducing a multimodality approach can significantly improve classification and prediction efficiency in neurodegenerative disorders.

Nano-Electrochemical Characterization of a 3D Bioprinted Cervical Tumor Model

Current cancer research is limited by the availability of reliable in vivo and in vitro models that are able to reproduce the fundamental hallmarks of cancer. Animal experimentation is of paramount importance in the progress of research, but it is becoming more evident that it has several limitations due to the numerous differences between animal tissues and real, in vivo human tissues. 3D bioprinting techniques have become an attractive tool for many basic and applied research fields. Concerning cancer, this technology has enabled the development of three-dimensional in vitro tumor models that recreate the characteristics of real tissues and look extremely promising for studying cancer cell biology. As 3D bioprinting is a relatively recently developed technique, there is still a lack of characterization of the chemical cellular microenvironment of 3D bioprinted constructs. In this work, we fabricated a cervical tumor model obtained by 3D bioprinting of HeLa cells in an alginate-based matrix. Characterization of the spheroid population obtained as a function of culturing time was performed by phase-contrast and confocal fluorescence microscopies. Scanning electrochemical microscopy and platinum nanoelectrodes were employed to characterize oxygen concentrations-a fundamental characteristic of the cellular microenvironment-with a high spatial resolution within the 3D bioprinted cervical tumor model; we also demonstrated that the diffusion of a molecular model of drugs in the 3D bioprinted construct, in which the spheroids were embedded, could be measured quantitatively over time using scanning electrochemical microscopy.

Multi-Omics Analysis Reveals Intratumor Microbes as Immunomodulators in Colorectal Cancer

Recent studies indicated that intratumor microbes are an essential part of the tumor microenvironment. Here, we performed an integrated analysis of genetic, epigenetic, and intratumor microbial factors to unravel the potential remodeling mechanisms of immune-cell infiltration (ICI) and tumorigenesis of colorectal cancer (CRC). We identified the components and structure of the intratumor microbiome as primary contributors to the difference in survival between ICI subtypes. Multiple tumor-infiltrating immune cells (TIICs) and immune-related genes were associated with intratumor microbial abundance. Additionally, we found that Clostridium was enriched in CRC patients who were nonsensitive to immune checkpoint blockade (ICB) therapy. We further provided clues that the intratumor microbes might influence the response to ICB therapy by mediating TIICs, especially MAIT (mucosa-associated invariant T) cells. Finally, three ICB-related TIICs and 22 of their associated microbes showed the potential to predict the response to ICB therapy (area under the receiver operating characteristic curve [AUC] = 89%). Our findings highlight the crucial role of intratumor microbes in affecting immune-cell infiltration patterns, prognosis, and therapy response of CRC and provide insights for improving current immunotherapeutic treatment strategies and prognosis for CRC patients. IMPORTANCE Using the multi-omics data from The Cancer Genome Atlas (TCGA) colorectal cancer (CRC) cohort, we estimated the tumor microenvironment (TME) infiltration patterns of patients and unraveled the interplay of gene expression, epigenetic modification, and the intratumor microbiome. This study suggests the impact of intratumor microbes on maintaining the tumor immune microenvironment in the pathogenesis of CRC and modulating the response to immune checkpoint blockade (ICB) therapy. We identified a set of combined features, including 3 ICB-related tumor-infiltrating immune cells (TIICs) and 22 of their associated microbes, that are predictive of ICB responses.

The mechanical phenotypic plasticity of melanoma cell: an emerging driver of therapy cross-resistance

Advanced cutaneous melanoma is the deadliest form of skin cancer and one of the most aggressive human cancers. Targeted therapies (TT) against BRAF mutated melanoma and immune checkpoints blockade therapies (ICB) have been a breakthrough in the treatment of metastatic melanoma. However, therapy-driven resistance remains a major hurdle in the clinical management of the metastatic disease. Besides shaping the tumor microenvironment, current treatments impact transition states to promote melanoma cell phenotypic plasticity and intratumor heterogeneity, which compromise treatment efficacy and clinical outcomes. In this context, mesenchymal-like dedifferentiated melanoma cells exhibit a remarkable ability to autonomously assemble their own extracellular matrix (ECM) and to biomechanically adapt in response to therapeutic insults, thereby fueling tumor relapse. Here, we review recent studies that highlight mechanical phenotypic plasticity of melanoma cells as a hallmark of adaptive and non-genetic resistance to treatment and emerging driver in cross-resistance to TT and ICB. We also discuss how targeting BRAF-mutant dedifferentiated cells and ECM-based mechanotransduction pathways may overcome melanoma cross-resistance.